The PGC is a large international consortium to pursue genome-wide analyses of common psychiatric disease including schizophrenia, bipolar disorder, autism, ADHD and major depressive disorder. The PGC is extending its investigations to include copy number variants and rare variants from sequencing studies, and is designing a PsychChip to study many putative risk alleles in very large samples.
A secondary, but important, focus of the PGC has been on the extent to which genetic observations are shared or unique across these major psychiatric diseases. The PGC's cross-disorder analysis (Lancet, 2013) manuscript (which used a number of methods developed by our group) reported on genome-wide data from 33,332 cases and 27,888 controls, indicating that specific risk SNPs are often associated with a range of neuropsychiatric outcomes.
Along with Sinai collaborator Pamela Sklar, Dr. Purcell has enjoyed a long-standing collaboration between investigators at the Karolinska Institutet (Christina Hultman), University of North Carolina (Patrick Sullivan) and the Stanley Center for Psychiatric Research (Jennifer Moran, Steve McCarroll). We have reported a primary genome-wide association study and CNV analysis (PubMed | PDF) as well as population genetic work (PubMed | PDF). We are continuing data collection and analysis of this sample. For example, a greatly expanded GWAS sample has led to more discoveries (Ripke et al. Nature Genetics, in press). We have also generated a large amount of exome sequence data on over 5,000 individuals from this population; our group is leading the ongoing analyses of these data.
The goal of the Bipolar Sequencing Consortium is to identify genetic variants that influence risk of bipolar disorder, by bringing together rare variant sequencing studies from both population-based and family-based studies. The groups involved are described here; for BSC investigators there is also a private resources page. Our group is heavily involved in the analysis of the population-based studies in particular.
We have collaborated extensively with researchers from the Centre for Neuropsychiatric Genetics and Genomics, University of Cardiff, Wales, on the analysis of a family-based sample of schizophrenia patients from Bulgaria. As well as polygenic (PubMed | PDF) and de novo CNV (PubMed | PDF) studies, we have recently completed exome sequencing of this sample for de novo single nucleotide variants. Working in close collaboration with the Cardiff investigators, our group spearheaded various aspects of the data generation and analytic pipelines. This work was in collaboration with the Sanger Institute (Aarno Palotie) and the Stanley Center for Psychiatric Research.
The ISC is a group of researchers from over dozen institutions who collaborated to perform large-scale genome-wide studies of schizophrenia. We published two prominent manuscripts describing our primary work, on the roles of common SNPs (PubMed | PDF) and rare copy number variants (PubMed | PDF) in predisposing to the disease (media coverage: BBC, Independent, NPR and NY Times). Furthermore, the ISC data have been used in a broad array of publications: for example, in following up individual associated loci ( 1, 2, 3, 4, 5, 6, 7 ), in broader analyses of genetic architecture ( 1, 2, 3, 4, 5 ), in population genetics ( 1, 2 ) and in methods development ( 1, 2, 3, 4, 5 ). The primary work of the ISC is now complete, although the data generated, and collaborative ethos, continues to be part of the PGC.
The International Cohort Collection for Bipolar Disorder (ICCBD) addresses the need for large-scale DNA and data resources to study bipolar disorder, by having established a uniquely large collection of samples and data from individuals with bipolar disorder. The aims of this project are 1) to ascertain and collect a large cohort of bipolar cases (N = 9000) and unaffected controls (N = 9000) over five years at two U.S. sites (Boston and Los Angeles) using novel high-throughput phenotyping methods; and 2) to construct a harmonized data resource for genetic studies combining phenotypic data from the U.S. case-control sample with a parallel, separately funded European case-control sample (10,000 cases and 10,000 controls) obtained from the UK and Sweden. Genotyping and genetic analyses of these resources will fully characterize common polymorphisms and copy number variants in the full sample to detect novel risk variants and attempt replication of the most compelling prior findings.
Members of our group are involved in collaboration with the BioMe project and the Institute for Personalized Medicine at Mount Sinai. The focus of this work is not primarily neuropsychiatric, but rather aims to leverage the rich clinical data existing in electronic medical records to discover novel genetic risk factors, and to focus on the ultimate translation of these findings back to the clinic.